A Review of Mechanistic Models for Predicting Adverse Effects in Sediment Toxicity Testing

Area of Science:

• Environmental Toxicology
• Risk Assessment
• Environmental Chemistry

Background:

• Bioavailability is critical for understanding chemical toxicity in sediments.
• Mechanistic modeling has evolved over 40 years to estimate exposure and predict adverse effects.
• Current review surveys the state of mechanistic modeling in contaminated sediment toxicity assessments.

Purpose of the Study:

• To provide an up-to-date survey of mechanistic modeling in contaminated sediment toxicity.
• To highlight advances, particularly for non-ionic organic contaminants and metals.
• To identify critical research needs for future model development.

Main Methods:

• Review of equilibrium partitioning-based (Eq-P) models for exposure estimation.
• Application of Abraham equations to estimate partition coefficients.
• Integration of species sensitivity distributions and toxicokinetic/toxicodynamic models.
• Modeling of contaminant mixtures, such as polycyclic aromatic hydrocarbons.

Main Results:

• Substantial advances in exposure modeling for non-ionic organic contaminants (NOCs) and divalent metals using Eq-P models.
• Successful prediction of sediment toxicity for NOCs and metals when combined with water-only effects data.
• Progress is less substantial for ionic/polar organic contaminants due to complex partitioning.
• Increasing application of species sensitivity distributions and TK/TD models.
• Successful modeling of adverse effects for contaminant mixtures like PAHs.

Conclusions:

• Mechanistic models are powerful tools for predicting contaminated sediment toxicity.
• Despite advances, critical research needs remain for further model development and application.
• Continued development is essential for informing environmental scientists, managers, and decision-makers on sediment risks.